Azure Data Factory vs. TIBCO Integration (including BusinessWorks and Flogo)

Best scenario is for ETL process. The flexibility and connectivity is outstanding. For our environment, SAP data connectivity with Azure Data Factory offers very limited features compared to SAP Data Sphere. Due to the limited modelling capacity of the tool, we use Databricks for data modelling and cleaning. Usage of multiple tools could have been avoided if adf has modelling capabilities.

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In BusinessWorks it is quite easy to develop applications and monitor where as it is not similar with Scribe. The data which successfully processed in Scribe is quite difficult to view. I think the Scribe console tool should have better view for the data it has processed.At times we founds some of our sales orders are missing which are unable to update/insert in the DB, after investigation found the issue is in Scribe tool. A case has been raised 02129657 for the same and as per the guidelines from the Scribe support engineer we did changes in the shutdown interval to zero. ''update SCRIBEINTERNAL.SCRIBE.KSYNC
set keyvalue= 0 where KEYNAME = 'SETTINGS.SHUTDOWNINTERVAL''. Later this change we started getting alert emails like ''Fatal error 325 occurred: Message processor shutting down
- defined maximum memory usage (900MB) exceeded. Please contact Scribe support
at support@scribesoft.com if this
problem persists''. We found this issue is a critical one as the occurrences of it is decreased but still it is persist.

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• Data Ingestion - it works very well with numerous data sources.
• Data pipeline orchestration: It is a generic, popular tool for orchestrating data pipelines.
• Works well in Azure ecosystem, Azure services and data platforms like Databricks.
• It is a serverless and scalable solution for cloud data integration.

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• The UI is easy to navigate and map flows are intuitive and easy to build upon after some basic training. However, a user should have some basic knowledge of writing nested statements.
• Very responsive customer support.
• The debug feature is a great tool for troubleshooting. You can easily identify where the issue is in your flow. At each debug step, it returns the expected value, and when there isn't the expected value, you know when to modify your flow.

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• Granularity of Errors: Sometimes, Azure Data Factory provides error messages that are too generic or vague for us, making it challenging to pinpoint the exact cause of a pipeline failure. Enhanced error messages with more actionable details would greatly assist us as users in debugging their pipelines.
• Pipeline Design UI: In my experience, the visual interface for designing pipelines, especially when dealing with complex workflows or numerous activities, can become cluttered. I think a more intuitive and scalable design interface would improve usability. In my opinion, features like zoom, better alignment tools, or grouping capabilities could make managing intricate designs more manageable.
• Native Support: While Azure Data Factory does support incremental data loads, in my experience, the setup can be somewhat manual and complex. I think native and more straightforward support for Change Data Capture, especially from popular databases, would simplify the process of capturing and processing only the changed data, making regular data updates more efficient

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• Missing functionality: We like to run all the files available in the FTP when clicking the run button. Right now, we have to click the run button several times (or have multiple solutions) in order to run files from our FTP site one at a time.
• Generating column fields every time a file changes from the source in the FTP is very tedious. Working in integrations makes me have to go back and forth a lot of the time, and doing this is incredibly annoying.
• The security is horrendous. We installed an on-premise agent on the customer side, but we don't want them even touching the ETL tool at all. The only knowledge we are fine with knowing and being able to see is that they installed the agent, not the solutions themselves.
• Our company's connector would have to point to the dataset name rather than dataset ID. It was very frustrating because we change the dataset name a lot, and then we'd have to repoint it.
• It's very difficult to monitor the different integrations that go on because there isn't a consolidated dashboard.

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We are deeply entrenched in using Tibco Scribe capabilities, and we are only expanding our usage. It would be one thing if we used it only for a one-time data load, but we have several Scribe maps running constantly, keeping business-critical data up to date. And the ease of use for the occasional, mass data update or upload is simply icing on the cake. I'm a big Microsoft fan, so there is potential down the road to convert our Scribe data integrations to Microsoft Flow (or Power Automate as it is now called). But for now, the functionality just isn't there with Flow (Power Automate), plus the work involved to change all our current integrations would be a large undertaking. So for now and the foreseeable future, Scribe will remain our data integration tool of choice.

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So far product has performed as expected. We were noticing some performance issues, but they were largely Synapse related. This has led to a shift from Synapse to Databricks. Overall this has delayed our analytic platform. Once databricks becomes fully operational, Azure Data Factory will be critical to our environment and future success.

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As mentioned in the previous sections, setup and maintenance is extremely easy. We don't have many issues for which we need support and there is no need for deep technical skills to use Tibco Cloud Integration platform. The solution provides everything we need for our specific use case, being the replication of our Microsoft Dynamics 365 CRM data to our on premise database for reporting.

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We have not had any issues with TIBCO not being available when needed. I have only had to contact support less than 5 times in about 5 year time frame due to syncing issues or a problem with the agent. Support is very quick to respond as well as very helpful.

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TIBCO Cloud Integration (including BusinessWorks and Scribe)'s performance of the user interface are not to be complained about. The user interface is swift and is a pleasant user experience. The replication jobs take some time to finish but that is because the number of records to be updated/created on a daily basis is quite big. I did split up the jobs between highrunners (entities with a lot of changes) I update on a daily basis and quite stable entities that I update weekly. That solved my issue of a way to long replication.

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We have not had need to engage with Microsoft much on Azure Data Factory, but they have been responsive and helpful when needed. This being said, we have not had a major emergency or outage requiring their intervention. The score of seven is a representation that they have done well for now, but have not proved out their support for a significant issue

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For creating new process, you have lots of palettes to do every develop you need. For created process it is easy to understand even if you have ever seen before it. You can analyze your process in all their detail. User Experience is positive for beginner and expertise people. Just debug mode is still raw, but better in TIBCO BusinessWorks 6.x than TIBCO BusinessWorks 5.x .

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Before using TIBCO Businessworks, I participated an official training with a specialized instructor. In this training, I learned what I needed to know to build some applications or web services and how to manage its. It was been very important to me. I understood many technical stuff to familiarize with this powerful platform. I can advice TIBCO Educational Services.

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really good resources

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If we don't design the process correctly, it can do lot of damage (like deleting files or data etc.,) and might assume product issue rather than a design flaw. So it is always recommended to do thorough unit testing , QA and a design review even for a small process to avoid major problems.

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Azure Data Factory helps us automate to schedule jobs as per customer demands to make ETL triggers when the need arises. Anyone can define the workflow with the Azure Data Factory UI designer tool and easily test the systems. It helped us automate the same workflow with programming languages like Python or automation tools like ansible. Numerous options for connectivity be it a database or storage account helps us move data transfer to the cloud or on-premise systems.

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Used TIBCO for migration of our data for our learning management system.TIBCO, succesful Content ,data migration(courses, classes, registrations, transcripts etc.) ,User migration(Internal users and Partner migration)and Report migrationIntegrations with different applications Workday,Single Sign-On,CertTracker,Okta,Partner contact sync and Questionmark is succesful.LOD: Learn on demand is a third party vendor application where all Virtual classes are delivered by the vendor application. Learning management system sends the class and registration events to learn on demand via real time web service call through TIBCO

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We could easily add multiple agents and new systems. This had no impact on the performance. We had some issues because flows cannot be splitted and called by each other. So you have lots of flows which are the same. It would be great if this was improved. Also transferring values via variables between flows seems to be impossible. You can only use global lists with dictionaries.

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• Facilitate better decision-making and improve business processes.
• Optimize business process outcomes by increasing internal efficiency and operational effectiveness.
• Boosts revenue growth while improving business process agility.

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• Startup time - the quick time in which we can provision integrations means we can deliver requirements quickly, which is what our departments need
• The online training means we can easily get users up and running without the need for the internal cost of training
• Development time - The development that was needed to create connectors for our custom application was large

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